Many industries use distributed, heterogeneous systems to make up larger multi-agent ecosystems. For the most part, coordination of these systems is managed manually with the control agents being humans. In some cases, humans cannot react fast enough. In other cases, the solution is not sufficiently robust and does not have an adequate backup. Also, human based systems are generally hard to scale. Facilities for humans are expensive to build and take time to construct. Training people for complex tasks is expensive, takes time and may not be possible or entirely effective for critical, rarely encountered edge cases. In disaster situations, these limitations can compound already trying situations.
Many existing systems, for the most part, work with heterogeneous equipment or a subset of all the equipment, and have little automation. Some solutions are not sufficiently flexible and have a concept of centralized control with a single master server/process. Other systems also depend on a Human Machine Interface (HMI) that requires users to process large data sets quickly. Still other solutions are not sufficiently robust due to manual processes, single point of failure and/or minimal redundancy. Most solutions have poor heterogeneous support working for one vendor and/or long lead times for new support.
The technology herein addresses these and other problems.